Remote Data Jobs • Go

We’re looking for a Senior Data Engineer to help build and scale a high-impact data platform that powers decision-making and innovation across engineering, legal, sales, marketing, and governance. You’ll play a critical role in designing real-time and batch data pipelines, ensuring data quality, privacy compliance, and accessibility through user-friendly portals and dashboards.

We're on the lookout for a Machine Learning Engineer to spearhead the evolution of our device intelligence and fingerprinting systems. This is a chance to lead groundbreaking projects that directly combat fraud and enhance security for millions. You will design and refine backend services using Go (Golang) to process and analyze device data, ensuring robustness and scalability.

As a Sr Data Engineer at SADA, you will ensure our customers’ support issues are handled effectively. You will work with highly skilled support engineers focused on providing Google Cloud Platform Data Engineering solutions, including BigQuery, Cloud SQL, Google Cloud Monitoring, and related Google services. The Data Engineer is responsible for providing technical assistance and guidance to team members and customers.

Identify, prioritize and execute tasks in the software development life cycle. Work with business to iterate over software requirements. Develop tools and applications by producing clean, efficient code. Automate tasks through appropriate tools and scripting. Analyze and debug systems. Proven experience in Data Engineering having expertise with big data, advanced AI integration, and SaaS apps.

As a Sr. Data Engineer you will enhance our B2B analytics platform by improving database schemas, data pipelines, and data structures in Snowflake to ensure optimally structured data is delivered to our customers on time and with high performance. Evaluate current solutions and implement strategic improvements across the entire data pipeline.

Architecting data platform infrastructure services on Snowflake and AWS using Python, Go, and Kubernetes for environment management, lifecycle automation, and drift detection at scale. Designing security controls including access management, data treatment frameworks, and attribute-based access controls that protect without hindering productivity. Building governance systems for data provenance, sovereignty enforcement, and automated compliance across jurisdictional boundaries.